longtermrisk/Llama-3.1-8B-school-of-reward-hacks-sft
The longtermrisk/Llama-3.1-8B-school-of-reward-hacks-sft is an 8 billion parameter Llama-3.1-based causal language model, fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct. Developed by longtermrisk, this model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. It is designed for general language tasks, leveraging its efficient training methodology.
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Model Overview
This model, longtermrisk/Llama-3.1-8B-school-of-reward-hacks-sft, is an 8 billion parameter language model fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct. It was developed by longtermrisk and utilizes the Llama-3.1 architecture.
Key Characteristics
- Base Model: Fine-tuned from Meta's Llama-3.1-8B-Instruct.
- Efficient Training: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Parameters: It features 8 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a context length of 8192 tokens.
Potential Use Cases
Given its Llama-3.1 base and efficient fine-tuning, this model is suitable for a variety of general-purpose natural language processing tasks, including:
- Instruction following
- Text generation
- Summarization
- Question answering